Jason Lines
Jason Lines
Lecturer in Computer Science, University of East Anglia
Verified email at uea.ac.uk - Homepage
Title
Cited by
Cited by
Year
The great time series classification bake off: a review and experimental evaluation of recent algorithmic advances
A Bagnall, J Lines, A Bostrom, J Large, E Keogh
Data Mining and Knowledge Discovery 31 (3), 606-660, 2017
5802017
Classification of time series by shapelet transformation
J Hills, J Lines, E Baranauskas, J Mapp, A Bagnall
Data Mining and Knowledge Discovery 28 (4), 851-881, 2014
3192014
Time-series classification with COTE: the collective of transformation-based ensembles
A Bagnall, J Lines, J Hills, A Bostrom
IEEE Transactions on Knowledge and Data Engineering 27 (9), 2522-2535, 2015
2682015
A shapelet transform for time series classification
J Lines, LM Davis, J Hills, A Bagnall
Proceedings of the 18th ACM SIGKDD international conference on Knowledge …, 2012
2642012
Time series classification with ensembles of elastic distance measures
J Lines, A Bagnall
Data Mining and Knowledge Discovery 29 (3), 565-592, 2015
2482015
Transformation based ensembles for time series classification
A Bagnall, L Davis, J Hills, J Lines
Proceedings of the 2012 SIAM international conference on data mining, 307-318, 2012
1162012
Time series classification with HIVE-COTE: The hierarchical vote collective of transformation-based ensembles
J Lines, S Taylor, A Bagnall
ACM Transactions on Knowledge Discovery from Data 12 (5), 2018
742018
Hive-cote: The hierarchical vote collective of transformation-based ensembles for time series classification
J Lines, S Taylor, A Bagnall
2016 IEEE 16th international conference on data mining (ICDM), 1041-1046, 2016
572016
Classification of household devices by electricity usage profiles
J Lines, A Bagnall, P Caiger-Smith, S Anderson
International conference on intelligent data engineering and automated …, 2011
552011
The UEA & UCR time series classification repository
A Bagnall, J Lines, W Vickers, E Keogh
URL http://www. timeseriesclassification. com, 2018
442018
An experimental evaluation of nearest neighbour time series classification
A Bagnall, J Lines
arXiv preprint arXiv:1406.4757, 2014
442014
Alternative quality measures for time series shapelets
J Lines, A Bagnall
International Conference on Intelligent Data Engineering and Automated …, 2012
392012
The UEA multivariate time series classification archive, 2018
A Bagnall, HA Dau, J Lines, M Flynn, J Large, A Bostrom, P Southam, ...
arXiv preprint arXiv:1811.00075, 2018
382018
On the segmentation and classification of hand radiographs
LM Davis, BJ Theobald, J Lines, A Toms, A Bagnall
International journal of neural systems 22 (05), 1250020, 2012
182012
Ensembles of elastic distance measures for time series classification
J Lines, A Bagnall
Proceedings of the 2014 SIAM International Conference on Data Mining, 524-532, 2014
172014
sktime: A unified interface for machine learning with time series
M Löning, A Bagnall, S Ganesh, V Kazakov, J Lines, FJ Király
arXiv preprint arXiv:1909.07872, 2019
142019
The heterogeneous ensembles of standard classification algorithms (HESCA): the whole is greater than the sum of its parts
J Large, J Lines, A Bagnall
arXiv preprint arXiv:1710.09220, 2017
132017
A probabilistic classifier ensemble weighting scheme based on cross-validated accuracy estimates
J Large, J Lines, A Bagnall
Data mining and knowledge discovery 33 (6), 1674-1709, 2019
112019
Simulated data experiments for time series classification Part 1: accuracy comparison with default settings
A Bagnall, A Bostrom, J Large, J Lines
arXiv preprint arXiv:1703.09480, 2017
92017
Is rotation forest the best classifier for problems with continuous features?
A Bagnall, M Flynn, J Large, J Line, A Bostrom, G Cawley
arXiv preprint arXiv:1809.06705, 2018
82018
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